A sound approach: Exploring a rapid and non-destructive ultrasonic pulse echo system for vegetable oils characterization

Opportunities and challenges of ultrasonic diagnostic techniques for plant-based food monitoring: principle, machine system, and application strategies

Plant-based food consumption has increased substantially owing to its positive effects on human and global health. However, ensuring the quality and safety of plant-based foods remains a challenge. Diagnostic ultrasonic technology is widely used for rapid and nondestructive determination owing to its ability to penetrate optically opaque materials, strong directivity, rapid detection capabilities, low equipment costs, and ease of operation. This review provides a comprehensive understanding of diagnostic ultrasonic technology by summarizing the principles of food characterization, factors that influence detection accuracy and methods to mitigate their impact, composition of ultrasonic machine systems, and application of diagnostic ultrasound for monitoring plant-based foods. The detection principle of ultrasonic technology is based on empirical equations that establish a relationship between the ultrasonic and physicochemical indicators of food. To improve the detection accuracy, a compensation mechanism for the temperature and pressure should be established, measurement distances should be set in the far-field region, and liquid samples should be degassed. Furthermore, the sample platform design and the choice of detection mode depend on the nature of the food. Combining ultrasonic technology with machine learning techniques presents promising prospects for real-time process monitoring in the food and beverage industries.

Temperature dependence of acoustic parameters in pure and blended edible oils: Implications for characterization and authentication

This research investigates the temperature-dependent variation of diverse acoustic parameters in samples of edible oils. It further supplements previous studies on the effectiveness of non-destructive ultrasonic inspection in the authentication of edible oils. The oils under examination consist of pure samples of olive, sunflower, and corn oils, as well as variable mixtures ranging from 20 % to 80 % of the more expensive one (olive oil) with the other two, simulating a hypothetical adulteration scenario. The studied acoustic parameters are related to the velocity, attenuation, and frequency components present in 2.25 MHz ultrasonic waves propagating through the oil samples within a temperature range of 24 °C to 34 °C. The results confirm the suitability of non-destructive ultrasonic inspection in evaluating and detecting the adulteration of olive oil with economically inferior oils such as sunflower and corn. Additionally, this study provides added value by laying the groundwork for a non-destructive and innovative determination of the fatty acid profile of an edible oil based on the evolution of the aforementioned ultrasonic parameters with temperature. The findings hold potential for enhancing the authenticity assessment and quality control of edible oils in the food industry.

Design, Fabrication, and Applications of SERS Substrates for Food Safety Detection: Review

Sustainable and safe food is an important issue worldwide, and it depends on cost-effective analysis tools with good sensitivity and reality. However, traditional standard chemical methods of food safety detection, such as high-performance liquid chromatography (HPLC), gas chromatography (GC), and tandem mass spectrometry (MS), have the disadvantages of high cost and long testing time. Those disadvantages have prevented people from obtaining sufficient risk information to confirm the safety of their products. In addition, food safety testing, such as the bioassay method, often results in false positives or false negatives due to little rigor preprocessing of samples. So far, food safety analysis currently relies on the enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), HPLC, GC, UV-visible spectrophotometry, and MS, all of which require significant time to train qualified food safety testing laboratory operators. These factors have hindered the development of rapid food safety monitoring systems, especially in remote areas or areas with a relative lack of testing resources. Surface-enhanced Raman spectroscopy (SERS) has emerged as one of the tools of choice for food safety testing that can overcome these dilemmas over the past decades. SERS offers advantages over chromatographic mass spectrometry analysis due to its portability, non-destructive nature, and lower cost implications. However, as it currently stands, Raman spectroscopy is a supplemental tool in chemical analysis, reinforcing and enhancing the completeness and coverage of the food safety analysis system. SERS combines portability with non-destructive and cheaper detection costs to gain an advantage over chromatographic mass spectrometry analysis. SERS has encountered many challenges in moving toward regulatory applications in food safety, such as quantitative accuracy, poor reproducibility, and instability of large molecule detection. As a result, the reality of SERS, as a screening tool for regulatory announcements worldwide, is still uncommon. In this review article, we have compiled the current designs and fabrications of SERS substrates for food safety detection to unify all the requirements and the opportunities to overcome these challenges. This review is expected to improve the interest in the sensing field of SERS and facilitate the SERS applications in food safety detection in the future.

High precision photoacoustic interferometer for the determination of the speed of sound in liquid media

In this work, we introduce the concept and delineate the fundamental principles of photoacoustic interferometry (PAInt), aiming at the development of a novel methodology for the precise assessment of the speed of sound in liquid media. The PAInt apparatus integrates an intensity-modulated continuous wave laser beam at 20 MHz for the efficient generation of monochromatic photoacoustic wavefronts which interfere across the surface of a vertically displaced spherically focused piezoelectric element. In this context, the resulting interference pattern can reveal the acoustic wavelength in the liquid medium with remarkable accuracy, providing thus reliable estimations of the speed of sound in reference liquids (error ∼0.1%) such as distilled and sea water, acetonitrile, and ethanol.

Detecting Food Fraud in Extra Virgin Olive Oil Using a Prototype Portable Hyphenated Photonics Sensor

Background

Current developments in portable photonic devices for fast authentication of extra virgin olive oil (EVOO) or EVOO with non-EVOO additions steer towards hyphenation of different optic technologies. The multiple spectra or so-called “fingerprints” of samples are then analyzed with multivariate statistics. For EVOO authentication, one-class classification (OCC) to identify “out-of-class” EVOO samples in combination with data-fusion is applicable.

Objective

Prospecting the application of a prototype photonic device (“PhasmaFood”) which hyphenates visible, fluorescence, and near-infrared spectroscopy in combination with OCC modelling to classify EVOOs and discriminate them from other edible oils and adulterated EVOOs.

Method

EVOOs were adulterated by mixing in 10–50% (v/v) of refined and virgin olive oils, olive-pomace olive oils, and other common edible oils. Samples were analyzed by the hyphenated sensor. OCC, data-fusion, and decision thresholds were applied and optimized for two different scenarios.

Results

By high-level data-fusion of the classification results from the three spectral databases and several multivariate model vectors, a 100% correct classification of all pure edible oils using OCC in the first scenario was found. Reducing samples being falsely classified as EVOOs in a second scenario, 97% of EVOOs adulterated with non-EVOO olive oils were correctly identified and ones with other edible oils correctly classified at score of 91%.

Conclusions

Photonic sensor hyphenation in combination with high-level data fusion, OCC, and tuned decision thresholds delivers significantly better screening results for EVOO compared to individual sensor results.

Highlights

Hyphenated photonics and its data handling solutions applied to extra virgin olive oil authenticity testing was found to be promising.

Non-Destructive Evaluation Device for Monitoring Fluid Viscosity

There is an increasing need for non-destructive, low-cost devices for real-time fluid viscosity monitoring. Therefore, in this study, a method based on structural health monitoring is adapted for monitoring fluid properties. A device is built such that an inexpensive and disposable viscosity probe be possible. The design incorporates a sensor/actuator pair using a piezoelectric material layered with copper/brass and capable of monitoring viscosity changes in low volume liquids (e.g., vacutainer vial). Experiments performed with the new device show a definite pattern of wave propagation in viscous solutions. A numerical model is built to investigate the wave propagation in the fluid. For experimental measurements, the sensor part of the device detects the generated pressure wave in fluid (e.g., air, water, glycerin) by the actuator part. The phase shift between the actuator and the sensor signals is then recorded and plotted for different concentrations of glycerin and water at room temperature. The results of this study show a direct correlation between the phase shift and varying viscosity in the ultrasonic frequency range from 6 to 9 MHz. The numerical simulation, performed utilizing acoustic modal and harmonic response analysis, results also demonstrate the same trend as the experimental results: a phase shift increases with the viscosity of the fluid.